Understanding Uncertainty in Probabilistic Floodplain Mapping in the Time of Climate Change

An integrated framework was employed to develop probabilistic floodplain maps, taking into account hydrologic and hydraulic uncertainties under climate change impacts. To the several scenarios representing individual compounding effects of models’ input parameters uncertainty were defined. Hydrologic model calibration validation performed using a Dynamically Dimensioned Search algorithm. A generalized likelihood estimation method used for quantifying uncertainty. draw on potential benefits proposed methodology, flash-flood-prone urban watershed in Greater Toronto Area, Canada, selected. The developed maps updated considering impacts with rainfall Intensity–Duration–Frequency (IDF) projections RCP8.5. results indicated that poses most delineation. Incorporating resulted expansion flood area an increase water depth. Comparison between stationary non-stationary IDFs showed probability is higher when approach used. large inevitable associated mapping increased future risk imply great need enhanced modeling techniques tools. are beneficial implementing management strategies land-use planning.